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And finally, it may also be the case Phone Number Database that you are looking for a correlation between X and Y, but you find a causal relationship between X and Z. For example, the makers of Sildenafil once tested the effects Phone Number Database of this drug on the development of heart cramps. . However, the male group of testers got an erection. Since then, the drug has been marketed as… Viagra. Pitfall 2. Look not only at averages, but Phone Number Database also at the extremes For years it was common in marketing to look at the averages. Today, we advise marketers to look at the extremes.

Of course it is very nice to know that Phone Number Database holiday park Twenhaarsveld in Holten scores an average of 8.5 based on the 620 reviews from visitors. That is a very decent score and many people will travel to the cozy Phone Number Database East on the basis of these figures. But in order to formulate a policy, Landal Phone Number Database would prefer to zoom in a little more closely on the results per activity it offers. For example, the pool only scores a 7.7 and visitors will know that this pool is quite dated. The other facilities at the park are of a much higher standard and this is also apparent from the figures.

Also read: Avoid drowning in Phone Number Database a data analysis [5 tips] At the next meeting with management, the park manager will argue for a little budget to refurbish the pool because chances are, if the figure drops below 7, people will choose another destination. Pitfall 3. Looking for trends in a cluttered bin of data – and then Phone Number Database drowning Another mistake is to focus on a bin of data looking for trends. But unless you're Google and have invested billions in artificial intelligence and pattern recognition, you'd better do it the other way around: try to see a proven conjecture in your bin of data.